Our objective is to establish the feasibility of a computational fluid dynamics (CFD)-based, left atrial (LA) regional blood flow analysis technology to predict stroke and abnormal brain MRI findings in patients with and without a history of atrial fibrillation (Afib), and to predict LA regional blood flow noninvasively following LA appendage (LAA) closure. Afib is a powerful risk factor for stroke and silent brain infarction (SBI), defined as evidence of brain infarction on imaging with no clinical symptoms. SBI accounts for cognitive decline associated with Afib, including cognitive impairment and dementia, in stroke-free individuals. Currently, there is an ongoing paradigm shift in our understanding of the mechanisms of stroke and SBI in patients with a history of Afib. A new paradigm is that alterations in LA structure and function during sinus rhythm are causally related to thromboembolism, and Afib is not mechanistically responsible for the thromboembolic events. This paradigm shift has uncovered an unprecedented opportunity to identify a high-risk subgroup by evaluating abnormal LA structure and function in a larger population, beyond patients with a history of Afib. Nevertheless, it remains unclear as to how abnormal LA structure and function during sinus rhythm, a solid mechanics process, alter the LA regional blood flow, a fluid mechanics process, to cause intracardiac thrombosis. Our central hypothesis is that LA regional blood flow in sinus rhythm can predict stroke and abnormal brain MRI findings more sensitively and specifically than LA structure and function in patients with or without a history of Afib. To quantify the three-dimensional (3-D) LA regional blood flow, we will use a CFD technology based on the patient-specific cardiac structure and function defined by cardiac CT. This technology can noninvasively estimate the 3-D regional blood flow within the left atrium as well as the LA appendage, the most common site of intracardiac thrombus, which would otherwise require invasive transesophageal echocardiography (TEE). We will apply the CFD technology to patients in the Johns Hopkins Cardiac CT Registry who underwent multidetector cardiac CT since 2004. We will determine the association of LA regional blood flow with subsequent stroke and abnormal brain MRI findings over 10 years. To quantify abnormal brain MRI findings, we will use an atlas-based brain MRI analysis, which is robust to ischemic changes and atrophy seen in our study population. We will also evaluate the feasibility of virtual LAA closure in silico by removing LAA from the pre-LAA closure CT to predict post-LAA closure LA regional blood flow noninvasively, which cannot be performed by any traditional imaging techniques. The proposed research will identify novel biomarkers to predict stroke and SBI in patients with and without a history of Afib, whereas the current guidelines allow risk stratification only in individuals with Afib; 2) it will provide evidence for studies to evaluate prophylactic OAC or LAA closure to reduce the risk of stroke, SBI, and cognitive decline; and 3) it will provide a new technology to guide catheter-based/surgical LAA closure based on patient-specific LA structure and function.